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LLM watermarking has attracted attention as a promising way to detect AI-generated content, with some works suggesting that current schemes may already be fit for deployment.
Information Hiding Techniques for Steganography and Digital Watermarking
Katzenbeisser, S. and Petitcolas, F. A · 2000
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Learning to detect and classify malicious executables in the wild
Kolter, J. Z. and Maloof, M. A · 2006
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Pegasus: Pre-training with extracted gap-sentences for abstractive summarization
Zhang, J., Zhao, Y., Saleh, M., and Liu, P. J · 2019
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Neural linguistic steganography
Ziegler, Z. M., Deng, Y., and Rush, A. M · 2019
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Exploring the limits of transfer learning with a unified text-to-text transformer
Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., Zhou, Y., Li, W., and Liu, P. J · 2020
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Adversarial watermarking transformer: Towards tracing text provenance with data hiding
Abdelnabi, S. and Fritz, M · 2021
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Membership inference attacks from first principles
Carlini, N., Chien, S., Nasr, M., Song, S., Terzis, A., and Tramèr, F · 2022
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Photorealistic text-to-image diffusion models with deep language understanding
Saharia, C., Chan, W., Saxena, S., Li, L., Whang, J., Denton, E. L., Ghasemipour, S. K. S., Lopes, R. G., Ayan, B. K., Salimans, T., Ho, J., Fleet, D. J., and Norouzi, M · 2022
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Paraphrastic representations at scale
Wieting, J., Gimpel, K., Neubig, G., and Berg-Kirkpatrick, T · 2022
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Distillation-resistant watermarking for model protection in NLP
Zhao, X., Li, L., and Wang, Y · 2022
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Sparks of artificial general intelligence: Early experiments with GPT-4
Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y. T., Li, Y., Lundberg, S. M., Nori, H., Palangi, H., Ribeiro, M. T., and Zhang, Y · 2023
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Can large language models be an alternative to human evaluations?
Chiang, D. C. and Lee, H · 2023
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Undetectable watermarks for language models
Christ, M., Gunn, S., and Zamir, O · 2023
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Towards possibilities & impossibilities of ai-generated text detection: A survey
Ghosal, S. S., Chakraborty, S., Geiping, J., Huang, F., Manocha, D., and Bedi, A. S · 2023
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RADAR: robust ai-text detection via adversarial learning
Hu, X., Chen, P., and Ho, T · 2023
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A watermark for large language models
Kirchenbauer, J., Geiping, J., Wen, Y., Katz, J., Miers, I., and Goldstein, T · 2023
Earlier work this paper cites.
Paraphrasing evades detectors of ai-generated text, but retrieval is an effective defense
Krishna, K., Song, Y., Karpinska, M., Wieting, J., and Iyyer, M · 2023
Cited alongside, same era.
A survey of text watermarking in the era of large language models
Liu, A., Pan, L., Lu, Y., Li, J., Hu, X., Wen, L., King, I., and Yu, P. S · 2023
Cited alongside, same era.
Detectgpt: Zero-shot machine-generated text detection using probability curvature
Mitchell, E., Lee, Y., Khazatsky, A., Manning, C. D., and Finn, C · 2023
Cited alongside, same era.
Are you copying my model? protecting the copyright of large language models for eaas via backdoor watermark
Peng, W., Yi, J., Wu, F., Wu, S., Zhu, B., Lyu, L., Jiao, B., Xu, T., Sun, G., and Xie, X · 2023
Cited alongside, same era.
Mark my words: Analyzing and evaluating language model watermarks
Piet, J., Sitawarin, C., Fang, V., Mu, N., and Wagner, D. A · 2023
Cited alongside, same era.
Free dolly: Introducing the world’s first truly open instruction-tuned llm, 2023
Conover, M., Hayes, M., Mathur, A., Xie, J., Wan, J., Shah, S., Ghodsi, A., Wendell, P., Zaharia, M., and Xin, R · 2024
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Proposal for a regulation of the european parliament and of the council laying down harmonised rules on artificial intelligence (artificial intelligence act) and amending certain union legislative acts - analysis of the final compromise text with a view to agreement
Council of the European Union · 2024
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Transforming the future of music creation, 2023a
Google DeepMind · 2024
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Identifying ai-generated content with synthid, 2023b
Google DeepMind · 2024
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On the learnability of watermarks for language models
Gu, C., Li, X. L., Liang, P., and Hashimoto, T · 2024
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On the zero-shot generalization of machine-generated text detectors
Pu, X., Zhang, J., Han, X., Tsvetkov, Y., and He, T · 2023
Cited alongside, same era.
Can ai-generated text be reliably detected?
Sadasivan, V. S., Kumar, A., Balasubramanian, S., Wang, W., and Feizi, S · 2023
Cited alongside, same era.
On second thought, let’s not think step by step! bias and toxicity in zero-shot reasoning
Shaikh, O., Zhang, H., Held, W., Bernstein, M. S., and Yang, D · 2023
Cited alongside, same era.
Necessary and sufficient watermark for large language models
Takezawa, Y., Sato, R., Bao, H., Niwa, K., and Yamada, M · 2023
Cited alongside, same era.
Gptzero: Towards detection of ai-generated text using zero-shot and supervised methods, 2023
Tian, E. and Cui, A · 2023
Cited alongside, same era.
Llama 2: Open foundation and fine-tuned chat models
Touvron, H., Martin, L., Stone, K., Albert, P., Almahairi, A., Babaei, Y., Bashlykov, N., Batra, S., Bhargava, P., Bhosale, S., Bikel, D., Blecher, L., Canton-Ferrer, C., Chen, M., Cucurull, G., Esiobu, D., Fernandes, J., Fu, J., Fu, W., Fuller, B., Gao, C., Goswami, V., Goyal, N., Hartshorn, A., Hosseini, S., Hou, R., Inan, H., Kardas, M., Kerkez, V., Khabsa, M., Kloumann, I., Korenev, A., Koura, P. S., Lachaux, M., Lavril, T., Lee, J., Liskovich, D., Lu, Y., Mao, Y., Martinet, X., Mihaylov, T., Mishra, P., Molybog, I., Nie, Y., Poulton, A., Reizenstein, J., Rungta, R., Saladi, K., Schelten, A., Silva, R., Smith, E. M., Subramanian, R., Tan, X. E., Tang, B., Taylor, R., Williams, A., Kuan, J. X., Xu, P., Yan, Z., Zarov, I., Zhang, Y., Fan, A., Kambadur, M., Narang, S., Rodriguez, A., Stojnic, R., Edunov, S., and Scialom, T · 2023
Cited alongside, same era.
Dipmark: A stealthy, efficient and resilient watermark for large language models
Wu, Y., Hu, Z., Zhang, H., and Huang, H · 2023
Cited alongside, same era.
Semstamp: A semantic watermark with paraphrastic robustness for text generation
Hou, A. B., Zhang, J., He, T., Wang, Y., Chuang, Y., Wang, H., Shen, L., Durme, B. V., Khashabi, D., and Tsvetkov, Y · 2024
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Unbiased watermark for large language models
Hu, Z., Chen, L., Wu, X., Wu, Y., Zhang, H., and Huang, H · 2024
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On the reliability of watermarks for large language models
Kirchenbauer, J., Geiping, J., Wen, Y., Shu, M., Saifullah, K., Kong, K., Fernando, K., Saha, A., Goldblum, M., and Goldstein, T · 2024
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Robust distortion-free watermarks for language models
Kuditipudi, R., Thickstun, J., Hashimoto, T., and Liang, P · 2024
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Raidar: generative AI detection via rewriting
Mao, C., Vondrick, C., Wang, H., and Yang, J · 2024
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Attacking LLM watermarks by exploiting their strengths
Pang, Q., Hu, S., Zheng, W., and Smith, V · 2024
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A robust semantics-based watermark for large language model against paraphrasing
Ren, J., Xu, H., Liu, Y., Cui, Y., Wang, S., Yin, D., and Tang, J · 2024
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Ghostbuster: Detecting text ghostwritten by large language models
Verma, V., Fleisig, E., Tomlin, N., and Klein, D · 2024
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Towards codable text watermarking for large language models
Wang, L., Yang, W., Chen, D., Zhou, H., Lin, Y., Meng, F., Zhou, J., and Sun, X · 2024
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Bypassing LLM watermarks with color-aware substitutions
Wu, Q. and Chandrasekaran, V · 2024
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Provable robust watermarking for ai-generated text
Zhao, X., Ananth, P., Li, L., and Wang, Y · 2024
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